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Cerebras
Cerebras provides a wafer-scale AI accelerator and software stack that enables single-node training of very large LLMs, high-throughput low-latency inference (GLM-4.6 at 1,000 TPS), PyTorch SDK, deployment options, and MLOps tooling.
Use Cases
- 🟢 Train and fine-tune extremely large language models (multi‑billion+ parameters) on a single node using Cerebras' wafer-scale AI accelerator and PyTorch SDK to eliminate complex distributed setups, accelerate iteration, and reduce total training time and cost.
- 🟢 Deploy production-grade low-latency, high-throughput LLM serving (e.g., GLM-4.6 at 1,000 TPS) using Cerebras to power customer-facing chat, recommendation, or search APIs while leveraging MLOps tooling for autoscaling and performance monitoring.
- 🟢 Build an end-to-end compliant AI deployment pipeline with Cerebras' SDK and MLOps stack—incorporating model versioning, observability, drift detection and audit logs—to safely roll out and monitor large models in regulated industries.